The Semantic Web: RPI ITWS Capstone (Fall 2012)

664 views

Published on

Overview/introduction to the Semantic Web for RPI ITWS Capstone class (Fall 2012)

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
664
On SlideShare
0
From Embeds
0
Number of Embeds
7
Actions
Shares
0
Downloads
12
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

The Semantic Web: RPI ITWS Capstone (Fall 2012)

  1. 1. ITWS Capstone Lecture:The Semantic Web John S. Erickson, Ph.D. Director, Web Science Operations Tetherless World Constellation RPI
  2. 2. ...the purpose of the lecture is to summarize the Semantic Web with key concepts and the introduction of a few advanced ideasthat will be useful to these graduating seniors in grad school or their careers... Greg Hughes
  3. 3. ...the purpose of the lecture is to summarize the Semantic Web with key concepts and the introduction of a few advanced ideasthat will be useful to these graduating seniors in grad school or their careers...
  4. 4. Boil the ocean!
  5. 5. What really matters?
  6. 6. Is this “Semantic Web” for real?
  7. 7. 1989...
  8. 8. 1989...““Vague but exciting...” Vague but exciting...”
  9. 9. 2001...
  10. 10. 2001...
  11. 11. 2001...
  12. 12. 2011...
  13. 13. 2011...
  14. 14. 2011...
  15. 15. 2011...
  16. 16. 2011...
  17. 17. 2011...
  18. 18. 2011...
  19. 19. Percent of total catalogs(from 192 catalogs) 19 19
  20. 20. Intl Open Govt Dataset Search:Percent of total catalogs searching 1,022,787 datasets(from 192 catalogs) from 192 catalogs in 24 languages representing 43 countries and international organizations (Summer 2012) 20 20
  21. 21. 2012...
  22. 22. 2012...
  23. 23. Semantic Web?
  24. 24. Semantic Web?“Web of meaning”
  25. 25. Semantic Web?“Web of meaning” Make meaningful Make meaningful assertions assertions about things about things on the Web... on the Web... Web of Data
  26. 26. Semantic Web? “Web of meaning” Web of DataLink ideas...Link ideas... Linked Data
  27. 27. Assertions...
  28. 28. ...about ideas???
  29. 29. subjectsubject predicate object object
  30. 30. subjectsubject predicate object objectarticlearticle has creator Jim Jim
  31. 31. doi:10.1109/MC.2009.30 http://purl.org/dc/elements/1.1/ creator http://dbpedia.org/resource/James_Hendler http://dbpedia.org/resource/James_Hendler
  32. 32. doi:10.1109/MC.2009.30 http://purl.org/dc/elements/1.1/ creator http://dbpedia.org/resource/James_Hendler http://dbpedia.org/resource/James_Hendler
  33. 33. Thats how to describe things...
  34. 34. ...but how do we find things?
  35. 35. SPARQL:pattern matchingover RDF graphs
  36. 36. http://bit.ly/RumkhW http://bit.ly/RumkhW?s?s dbpedia2:blackboard ?blackboard ?blackboard
  37. 37. http://bit.ly/Rumtlp http://bit.ly/Rumtlp?s?s dbpedia2:blackboard ?blackboard ?blackboard
  38. 38. http://bit.ly/RumQwuhttp://bit.ly/RumQwu
  39. 39. http://bit.ly/RumQwu http://bit.ly/RumQwu “There is no such month?s?s dbpedia2:blackboard “There is no such month as “Rocktober” as “Rocktober”
  40. 40. http://bit.ly/RumQwuhttp://bit.ly/RumQwu
  41. 41. http://bit.ly/RumQwu http://bit.ly/RumQwuhttp://dbpedia.org/resource/Double,_Double,_Boy_in_Troublehttp://dbpedia.org/resource/Double,_Double,_Boy_in_Trouble
  42. 42. When in 2009 The Inventor said unto us...
  43. 43. Use URIs as names for thingsUse URIs as names for thingsUse HTTP URIs so that people can look up Use HTTP URIs so that people can look upthose names (on the Web) those names (on the Web)When someone looks up a URI, return When someone looks up a URI, returnuseful information, using the standards useful information, using the standards((RDF*,SPARQL)) RDF*, SPARQLInclude links to other URIs, so that they can Include links to other URIs, so that they candiscover more things discover more things
  44. 44. Use URIs as names for thingsUse URIs as names for thingsUse HTTP URIs so that people can look up Use HTTP URIs so that people can look upthose names (on the Web) those names (on the Web)When someone looks up a URI, return When someone looks up a URI, returnuseful information, using the standards useful information, using the standards((RDF*,SPARQL)) RDF*, SPARQLInclude links to other URIs, so that they can Include links to other URIs, so that they candiscover more things discover more things
  45. 45. The Linked Data CloudThe Linked Data Cloud
  46. 46. The Linked Data CloudThe Linked Data Cloud
  47. 47. The Linked Data CloudThe Linked Data Cloud
  48. 48. How does this help us?
  49. 49. Linked Data enables agile data integration andapplication creation
  50. 50. Mashup: OrgPedia Open Corporate DataMashup: OrgPedia Open Corporate Data http://tw.rpi.edu/orgpedia/
  51. 51. Mashup: RPI Research CentersMashup: RPI Research Centers
  52. 52. Mashup: RPI Research CentersMashup: RPI Research Centers
  53. 53. Mashup: Research DataMashup: Research Data
  54. 54. Mashup: Research DataMashup: Research Data
  55. 55. Example: Extending a Sci Publishing PortalExample: Extending a Sci Publishing Portal
  56. 56. Example: Extending a Sci Publishing PortalExample: Extending a Sci Publishing Portal
  57. 57. Idea: Linking Data-driven Apps with “Smart Content” http://inference-web.org/wiki/Semantic_Water_Quality_Portal http://inference-web.org/wiki/Semantic_Water_Quality_Portal
  58. 58. [data integration/data science]
  59. 59. Schematic for Deep Carbon Virtual Observatory and Interoperability SemanticIntegrated Discovery interoperability Analytics Global Census, Virtual visualizations and mining Mineral Laboratory, ...Applications Application-level mediation: vocabulary, mapping to science and data terms SemanticSoftware, Deep Energy/ interoperability Physics/ …. Res/Flux Life Chemistry ApplicationsTools & Apps Applications Models Semantic query, Q uery, hypothsis and access and inference use of data Semantic mediation: physics, chemistry, mineral, emission data - ChemML, Metadata, Data schema, Emission/ data GVP MINDAT EOS EarthChem Compositions Repositories ... ... ...
  60. 60. ...the purpose of the lecture is to summarize the Semantic Web with key concepts and the introduction of a few advanced ideasthat will be useful to these graduating seniors in grad school or their careers...
  61. 61. Semantic Web key concepts... RDF, SPARQL, Linked Data, mashups, dataviz,RDFa, microformats, Schema.org
  62. 62. Semantic Web key concepts... advanced ideas... RDF, SPARQL, ontology, inference, Linked Data, reasoning, provenance, mashups, dataviz, machine learning,RDFa, microformats, policy-based systems Schema.org
  63. 63. Semantic Web key concepts... advanced ideas... RDF, SPARQL, ontology, inference, Linked Data, reasoning, provenance, mashups, dataviz, machine learning,RDFa, microformats, policy-based systems Schema.org careers...
  64. 64. ????

×